Microsatellite instability (MSI), resulting from a defective mismatch repair system, occurs in approximately 15% of sporadic colorectal cancers (CRC). Since MSI is associated with a poor response to 5-fluorouracile based chemotherapy and is a positive predictive marker of immunotherapy, it is routine practice to evaluate the MSI status of resected tumors in CRC patients.
Trang 1R E S E A R C H A R T I C L E Open Access
Validation of computational determination
of microsatellite status using whole exome
sequencing data from colorectal cancer
patients
Amanda Frydendahl Boll Johansen1†, Christine Gaasdal Kassentoft1†, Michael Knudsen1, Maria Bach Laursen1, Anders Husted Madsen2, Lene Hjerrild Iversen3, Kåre Gotschalck Sunesen4, Mads Heilskov Rasmussen1and
Claus Lindbjerg Andersen1*
Abstract
Background: Microsatellite instability (MSI), resulting from a defective mismatch repair system, occurs in approximately 15% of sporadic colorectal cancers (CRC) Since MSI is associated with a poor response to 5-fluorouracile based chemotherapy and is a positive predictive marker of immunotherapy, it is routine practice to evaluate the MSI status of resected tumors in CRC patients MSIsensor is a novel computational tool for determining MSI status using Next Generation Sequencing However, it is not widely used in the clinic and has not been independently validated in exome data from CRC To facilitate clinical implementation of computational determination of MSI status, we compared MSIsensor to current gold standard methods for MSI testing
Methods: MSI status was determined for 130 CRC patients (UICC stage I-IV) using immunohistochemistry, PCR based microsatellite stability testing and by applying MSIsensor to exome sequenced tumors and paired germline DNA Furthermore, we investigated correlation between MSI status, mutational load and mutational signatures Results: Eighteen out of 130 (13.8%) patients were microsatellite instable We found a 100% agreement between MSIsensor and gold standard methods for MSI testing All MSI tumors were hypermutated In addition, two microsatellite stable (MSS) tumors were hypermutated, which was explained by a dominant POLE signature and pathogenic POLE mutations (p.Pro286Arg and p.Ser459Phe)
Conclusion: MSIsensor is a robust tool, which can be used to determine MSI status of tumor samples from exome sequenced CRC patients
Keywords: MSIsensor, Colorectal cancer, DNA mismatch repair deficiency, Microsatellite instability, MSI, MSS, POLE, Exome sequencing
Background
Colorectal cancer (CRC) is the third most common
can-cer worldwide and the second leading cause of cancan-cer-
(TNM) staging is the general parameter used for guiding
addition, the molecular subtype of the tumor influences treatment decisions and outcome While most sporadic CRC tumors develop through the chromosomal instable (CIN) pathway, close to 15% develop via the microsatel-lite instability (MSI) pathway [3, 4] Moreover, MSI is a hallmark of hereditary Lynch-syndrome related cancer
(dMMR) system resulting in hypermutation due to slip-page of the DNA polymerase during replication This is most evident in microsatellites structures, which are
© The Author(s) 2019 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/ ), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made The Creative Commons Public Domain Dedication waiver
* Correspondence: cla@clin.au.dk
†Amanda Frydendahl Boll Johansen and Christine Gaasdal Kassentoft
contributed equally to this work.
1 Department of Molecular Medicine, Aarhus University Hospital, Palle
Juul-Jensens Boulevard 99, DK-8200 Aarhus N, Denmark
Full list of author information is available at the end of the article
Trang 2defined as repeating sequences of 2–6 nucleotides
occur-ring throughout the genome [4] Generally, patients with
MSI tumors have a better prognosis than stage-matched
microsatellite stable and CIN tumors [4] Furthermore,
while MSI patients respond inferiorly to standard
positive predictive marker of immunotherapy [7]
There-fore, it is recommended to screen all resected CRC
tumors for dMMR to stratify treatment options [8]
Routine testing for dMMR is performed by
immuno-histochemically (IHC) quantification of the MMR
often complemented by a polymerase chain reaction
(PCR) based assessment of the stability of a five
quasi-monomorphic mononucleotide repeats, referred to as
pentaplex PCR [8, 13–15] Both methods are laborious,
time-consuming, limited to a small set of analytical
tar-gets and to some extent involves subjective
interpret-ation With the increasing use of Next Generation
Sequencing (NGS) in cancer diagnostics, various
compu-tational tools have been developed aiming to determine
the microsatellite status using an increased number of
microsatellite regions [16–18] These tools have the
potential to determine MSI status directly from NGS
data, without the need for additional biological testing
shown promising results [17,19,20] So far, the reported
MSIsensor results have primarily been produced using
per-formance of MSIsensor on whole exome sequenced data
Here, we benchmarked the accuracy of MSIsensor
against gold standard IHC and pentaplex PCR analyses
in a cohort of 130 exome sequenced CRC patients We
aimed to justify the use of MSIsensor in the clinic as a
replacement of the current pentaplex PCR and IHC
practice
Methods
Samples
Patients with UICC stage I-IV CRC were recruited
between May 2014 and January 2017 at the Surgical
Departments of Aarhus University Hospital, Randers
Hospital and Herning Hospital Tumor and matched
germline DNA from buffy coat were collected at surgery
molecular testing, including microsatellite stability
evalu-ation, were included in this study Four patients
presented with synchronous tumors From these, we
randomly selected one tumor We note that
synchron-ous tumors in all cases were classified alike by gold
standard methods (IHC and pentaplex PCR) and
MSI-sensor (data not shown)
Immunohistochemical and pentaplex PCR assessment of microsatellite status
IHC was performed as part of the routine diagnostic work-up and the results were extracted from patient hospital files In brief, the presence or absence of nuclear expression of MLH1, MSH2, MSH6 and PMS2 was assessed in the tumor cells Tumors were defined as mismatch repair proficient if all four proteins were expressed and mismatch repair deficient if any of the four proteins were not expressed
Analysis of MSI status by PCR was performed at Department of Molecular Medicine (Aarhus University Hospital) using a panel of the five mononucleotide microsatellite loci; BAT-25, BAT-26, NR-21, NR-22 and NR-24 as previously described [14,15] (Additional file1: Table S1) Tumors were classified as MSI when three or more markers showed instability, i.e changed pattern compared to a normal control sample If less than three markers were unstable, the tumors were classified as MSS A sample was classified as MSI if any of the methods scored the sample as dMMR or MSI Other-wise, the sample was classified as MSS
Whole exome sequencing
Paired tumor derived from freshly frozen or formalin-fixed paraffin-embedded tissue and germline DNA from buffy coat were sequenced using paired-end (2 × 150 bp) whole exome sequencing with the MedExomePlusV1_ hg19 panel (Roche, 72.28 Mb), as previously described
mapped to the reference genome (GRCh37/hg19) using
Table 1 Patient characteristics and demographics
Age at surgery, median (range) 67.8
(43 –91) Gender, n (%)
Pathological UICC stage, n (%)
MSS/MSI status, n (%)
a Four patients had synchronous cancers One sample was chosen randomly from each patient
Trang 3Picard MarkDuplicates [27], and the alignment was
fur-ther processed using GATK IndelRealigner and
BaseReca-librator according to the GATK Best Practices (v3.7) [28]
MSIsensor
We applied MSIsensor (version 0.5) using default
pa-rameters to facilitate interpretation and translation to
other laboratory facilities MSIsensor identifies
somatic-ally mutated microsatellite loci in NGS data using a
two-step process, which first involves scanning the reference
genome for microsatellite sites Sites are considered as
microsatellites only if the sequence motif is at most five
bases long and repeated at least three times
Microsatel-lite sites with less than 20 mapped reads in tumor or
germline are not considered The second part of the
analysis uses a χ2
test to identify mutated microsatellites
by comparing the distributions of homopolymer lengths
in the tumor and normal samples at the sites identified
in the first step The resulting MSIsensor score is a value
between 0 and 100 that corresponds to the percentage
of mutated microsatellite loci The tumors were
classi-fied as MSI if the score was greater than or equal to 3.5
and MSS if less than 3.5, which is the suggested cut-off
for exome sequenced samples in the original MSIsensor
publication [16]
Mutational load and mutational signatures
Somatic variants (SNVs and INDELs) were called using
MuTect2 filters were further evaluated and retained if
mu-tational burden was calculated as the total number of
variants per targeted mega base (Mb) We used k-means
clustering to differentiate hypermutated tumors from
non-hypermutated tumors
COSMIC mutational signatures (Version 2) were
mutational sum greater than 50, thereby fulfilling the
recommended criterion for assessing the mutational
signature [30]
POLE mutation status and classification
Variants were annotated using SnpEff (version 4.3.1)
including two bases into introns on both sides of each
exon Variants with an allele frequency less than 10%
were discarded The remaining variants were inspected
in Integrated Genomics Viewer (version 2.4.9) [32] and
classified as“pathogenic”, “likely pathogenic”, “variant of
uncertain significance”, “likely benign” and “benign”
according to the American College of Medical Genetics
Variant Analysis (version 5.4.20190121) [34]
Further-more, it was evaluated whether the variant was a common
somatic variant, defined as seen somatic more than three independent times in the literature, as an extra layer to the classification
Results
MSIsensor accurately classify MSI status in CRC patients
One-hundred thirty CRC patients were enrolled in this study The microsatellite status was initially determined
by gold standard methods IHC (n = 126) and pentaplex
high agreement between the methods (Cohens Kappa 0.96) As described in Methods, samples were classified
as MSI if tested positive by either of the gold standard methods From this, 18 patients (13.8%) were classified
as MSI
Using exome sequencing data from matched tumor and germline DNA from buffy coat, the MSIsensor scores were calculated and compared to microsatellite status determined by IHC and pentaplex PCR With the recommended cut-off at 3.5, MSIsensor correctly classi-fied all 130 patients into MSI (n = 18) and MSS (n = 112) (Fig.1) The mean MSIsensor score was significantly dif-ferent between MSI tumors (mean 24.2; range 10.4– 38.6) and MSS tumors (mean 0.3; range 0–1.37) (p = 1.97∗ 10− 10, Welch Two Sample t-test)
Sequencing duplicates influence the MSIsensor score
In the original publication by Niu et al., MSIsensor does not account for sequencing duplicates [16] In order to investigate the effect of sequencing duplicates the flagged duplicates were removed prior to running the MSIsensor The mean duplication rate for tumor and germline were 24.5% (range 10.2 -65.9%) and 11.2% (range 6.2 - 24.4%) respectively (Additional file1: Table S3) If sequencing duplicates were not removed prior to application of MSIsensor, we observed an elevated MSI-sensor score for 121 samples, a slight decrease for two samples while the MSIsensor score was unaltered for
increase in MSIsensor score with sequencing duplicates were 2.65 (p = 6.46 ∗ 10− 6, paired t-test) for MSI samples and 0.3 (p = 6.57 ∗ 10− 14, paired t-test) for MSS samples This translate to an 11% increase for MSI samples and 126% increase for MSS samples
MSIsensor classification is associated with hypermutation and dMMR mutational signatures
MSI cancers are known to be hypermutated [4] In agree-ment, we found significantly higher mutational load in MSI tumors classified by MSIsensor (median 90.1 muta-tions/Mb; range 69.2–217.8) as compared to MSS tumors (median 6.1 mutations/Mb; range 2.6–294.8) (p = 1.09 ∗
10− 11, Wilcoxon rank sum test) (Fig.2) We found signifi-cantly more dMMR-associated signatures (signatures 6,
Trang 415 and 26) in MSI (14 out of 18) as compared to MSS (12
out of 112) tumors (p = 8.96 ∗ 10− 9, Fishers Exact test)
(Fig.3, Additional file1: Table S4) Interestingly, two MSS
tumors had a hypermutation phenotype with more than
150 mutations/Mb (Patients 1 and 4) Mutational
ture analysis of these tumors showed a dominant
(POLE) [35] Mutational analysis of the exome data con-firmed that both tumors had pathogenic POLE mutations (patient 1: p.Pro286Arg, patient 4: p.Ser459Phe, Add-itional file1: Table S5) located in the exonuclease domain
of POLE, which are known to cause a hypermutated phenotype [36, 37] A third tumor (Patient 24) showed a
Fig 1 Distribution of MSIsensor scores The distribution of MSIsensor scores according to classification by gold standard methods (pentaplex PCR and/or IHC) Red and black points indicate MSI and MSS tumors as classified by the MSIsensor, respectively Dashed grey line shows the cut-off of 3.5% used to differentiate MSI from MSS
Fig 2 Mutational load of tumor samples Mutational load per million bases (Mb) in tumor Samples are ordered according to mutational load Red bars indicate MSI tumors, whereas black bars indicate MSS tumors Grey lines below the plot indicates the separation between hypermutated samples (dark grey) and samples with low mutational load (light grey)
Trang 5minor contribution from POLE signature 10 (6.6%)
How-ever, the tumor was not classified as hypermutated (10.23
POLE mutation We identified additional 12 tumors with
potential pathogenic somatic POLE mutations
(Add-itional file1: Table S5) However, these mutations were all
located outside the exonuclease domain and the tumors
did not show any signs of a POLE signature
Discussion
Evaluation of MSI status is important for the assessment
important for the guidance of immunotherapy as FDA
approved pembrolizumab for unresectable or metastatic
In addition to MSI status, mutational load is also
being investigated as a biomarker for immunotherapy
[39–41] Thus, MSI status as well as mutational load
is likely to improve treatment stratification of cancer
patients The increasing use of NGS in the diagnostic
work-up of cancer patients offers a great potential for
assessing both MSI status as well as mutational load
Various tools have been developed to assess the MSI
provide sufficient evidence to use MSIsensor as the
sole method for determination of MSI status, thereby
offering an objective assessment of MSI status
Currently, IHC and pentaplex PCR are the methods of choice to determine MSI status in the clinic Although widely used, discrepancy is commonly reported between the methods [42–44] This was exemplified in our data where one sample was classified as MSS with IHC but as MSI using the pentaplex assay Such inconsistencies demonstrate that both methods are indeed required to evaluate MSI status robustly in patients, and emphasizes the need for a single unambiguous method
The majority of studies applying MSIsensor have used data from a small cancer specific panel (MSK-IMPACT
distribution of microsatellite loci within a panel, these studies used a panel specific score of 10% to classify samples as MSI [19,20] Only a limited number of stud-ies have applied MSIsensor on exome data [17,46, 47], despite the fact that this is a widely used panel in cancer diagnostics A study by Kautto et al used exome data from TCGA (colon adenocarcinoma/rectal adenocarcin-oma (COAD/READ) and uterine corpus endometrioid cancer (UCEC) cohorts) [17] to investigate the perform-ance of various computational tools for MSI testing, including MSIsensor This is partly the same data, which originally was used to developed MSIsensor (UCEC cohort) [16] The current study is the first to validate the performance of MSIsensor in an independent exome sequenced cohort In addition, to encourage MSIsensor implementation in routine laboratories, we used default
Fig 3 Mutational signatures of tumor samples Cosmic mutational signatures of tumor samples, given in percentage (%) Samples are ordered according to mutational load (comparable to Fig 2 ) Color of bar represent mutational signatures as shown in the legend with signature number and proposed etiology The MSI status of the samples is denoted below the plot with red (MSI) or black (MSS) lines
Trang 6settings similar to the original MSIsensor publication,
in-cluding a cutoff threshold of 3.5 Our results
docu-mented excellent agreement between the classification
by MSIsensor and orthogonal methods, suggesting that
MSIsensor analysis of exome sequenced tumors may
replace gold standard methods to assess the MSI status
of CRC patients As MSIsensor was originally developed
using UCEC exome data, our validation in an
independ-ent CRC cohort further suggests that MSIsensor may be
used in various exome sequenced cancers with success
The fact that MSIsensor has been successfully applied in
sequenced samples supports this notion However,
fur-ther independent validations specifically in exome data
from various cancers is warranted
We have investigated how sequencing duplicates
influ-ence the MSIsensor score We observed a significantly
higher MSIsensor score when duplicates were not
removed The effect of sequencing duplicates on the
MSIsensor score is most easily explained by PCR errors
during NGS library preparation and sequencing
Homo-polymeric loci are especially vulnerable in this regard,
thus increasing the chance of obtaining significantly
different length distributions between tumor and
germ-line samples Even though the MSI classification in our
cohort was not altered, we recommend that researchers
remove duplicates prior to application of MSIsensor to
avoid false positive MSI classification
While we found an excellent agreement between
MSIsensor and gold standard methods to detect
dMMR, the COSMIC mutational signatures did not
identify all samples with dMMR The COSMIC
muta-tional signatures aim to classify mutamuta-tional patterns
associated with environmental and biological processes
A deficient mismatch repair system has been associated
with signatures 6, 15, 20 and 26 [35, 48] Signature 20
was not seen in any of our samples, which probably
reflects its low frequency in cancers, in general [35]
We found dMMR signatures in 14 of the 18 (78%) MSI
samples, while 12 out of 112 (10.7%) MSS samples also
revealed signatures associated with dMMR This clearly
shows that mutational signatures cannot be used as a
standalone test for determining whether a patient has a
defective mismatch repair system Rather, mutational
signatures may be helpful in order to explain the
underlying biological processes in the tumor This was
true for the two hypermutated samples with signature
10 (POLE signature, Patient 1 and 4), which had
patho-genic POLE mutations This information might be used
for guiding the patients into clinical trials Currently,
clinical trials are enrolling patients with mutations in
genes, POLE and POLD1, to determine the
effective-ness of immunotherapy in these patients (ClinicalTrials
Conclusion Here, we have validated MSIsensor as a robust tool, which can be used to determine the MSI status of tumor samples from exome sequenced CRC patients with standard settings and the recommended cut-off We found a 100% agreement between MSIsensor and orthogonal gold stand-ard methods (IHC and pentaplex PCR) for MSI testing Thus, MSIsensor provide a cost-efficient method to facili-tate the analysis of CRC patients, which can be integrated
in routinely genetic testing of patients
Supplementary information Supplementary information accompanies this paper at https://doi.org/10 1186/s12885-019-6227-7
Additional file 1: Table S1 Primers and probes for pentaplex PCR Table S2 Microsatellite status determined by various methods Table S3 MSIsensor output from all patients Table S4 Mutational signatures and MSI classification of patients Table S5 POLE mutations identified in patient cohort.
Abbreviations
5-FU: 5-fluorouracile; ACMG guidelines: American College of Medical Genetics; CIN: Chromosomal instable; COAD/READ: Colon adenocarcinoma/ rectal adenocarcinoma; COSMIC: Catalogue of somatic mutations in cancer; CRC: Colorectal cancer; dMMR: Deficient mismatch repair; FDA: Food and Drug Administration; IHC: Immunohistochemistry; Mb: Mega base;
MSI: Microsatellite instable; MSK-IMPACT: Memorial Sloan Kettering-Integrated Mutation Profiling of Actionable Cancer Targets; MSS: Microsatellite stable; NGS: Next Generation Sequencing; PCR: Polymerase chain reaction; POLD1: Polymerase delta 1; POLE: Polymerase epsilon; UCEC: Uterine corpus endometrioid cancer
Acknowledgements
We thank the patients for participating and contributing biological material and the Danish Cancer Biobank is acknowledged for providing access to the materials.
Authors ’ contributions AFBJ and CGK contributed to study design, data analysis, interpretation of data and drafting of the manuscript MK contributed to data analysis MBL contributed to study design AHM, LHI and KGS recruited the patients and collected all biological specimens MHR contributed to data analysis and drafting of manuscript CLA contributed to the study design, supervised the study and revised the manuscript All authors have read and approved the final manuscript.
Funding Grants from the Danish Cancer Society (R107-A7935, R133-A8520 –00-S41, R146-A9466 –16-S2) and the Novo Nordisk Foundation (NNF14OC0012747, NNF17OC0025052).
These funders had no role in the study design, the collection of samples, analysis and interpretation of data, and writing the manuscript.
Availability of data and materials The datasets generated and/or analyzed during the current study are not publicly available due to Danish personal data protection regulations, but may be made available for specific analysis upon approval from the relevant Danish authorities.
Ethics approval and consent to participate The study was approved by the Committees on Biomedical Research Ethics
in the Central Region of Denmark (reference id: 1-10-72-223-14) The study was performed in accordance with the Declaration of Helsinki All partici-pants provided written informed consent.
Trang 7Consent for publication
Not applicable
Competing interests
The authors declare that they have no competing interests.
Author details
1 Department of Molecular Medicine, Aarhus University Hospital, Palle
Juul-Jensens Boulevard 99, DK-8200 Aarhus N, Denmark 2 Department of
Surgery, Herning Regional Hospital, Herning, Denmark 3 Department of
Surgery, Aarhus University Hospital, Aarhus, Denmark.4Department of
Surgery, Randers Regional Hospital, Randers, Denmark.
Received: 28 June 2019 Accepted: 9 October 2019
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